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Journal articles on the topic 'Hybrid methodology'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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1

Caginalp, G., and V. Ilieva. "Hybrid methodology for technical analysis." Nonlinear Analysis: Hybrid Systems 2, no. 4 (2008): 1144–51. http://dx.doi.org/10.1016/j.nahs.2008.09.007.

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2

Skolud, B., and A. Szopa. "Production planning methodology in hybrid systems." IOP Conference Series: Materials Science and Engineering 400 (September 18, 2018): 062027. http://dx.doi.org/10.1088/1757-899x/400/6/062027.

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3

Klocke, Fritz, Andreas Roderburg, and Christoph Zeppenfeld. "Design methodology for hybrid production processes." Procedia Engineering 9 (2011): 417–30. http://dx.doi.org/10.1016/j.proeng.2011.03.130.

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4

Bennington, Lynne, and James Cummane. "Measuring service quality: A hybrid methodology." Total Quality Management 9, no. 6 (1998): 395–405. http://dx.doi.org/10.1080/0954412988343.

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5

Ting, Jacky Siu-Lun, Siu-Keung Kwok, and Albert Hing-Choi Tsang. "Hybrid Risk Management Methodology: A Case Study." International Journal of Engineering Business Management 1 (March 2009): 3. http://dx.doi.org/10.5772/6783.

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6

Pereira, Teresa, and Fernanda A. Ferreira. "An ERP selection using a hybrid methodology." Journal of Computational Methods in Sciences and Engineering 20, no. 3 (2020): 689–95. http://dx.doi.org/10.3233/jcm-194011.

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With this work, we developed a multi-criteria decision-making model to assess and select an Enterprise Resource Planning (ERP), using a multi-criteria decision analysis (MCDA). A hybrid multi-criteria methodology is used for the assessment and selection of an ERP, combining the MMASSI/IT methodology, which is used to both define the relevant family of criteria, based on their features and flexibility to change and adapt to a given scope, and the weight of criteria. Then, the well-known Analytic Hierarchy Process (AHP) methodology is used to perform the decision-makers’ value function elicitati
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7

Gradeci, K., and M. Sletnes. "The Hybrid-Agile Design of Experiments Methodology." Journal of Physics: Conference Series 2069, no. 1 (2021): 012039. http://dx.doi.org/10.1088/1742-6596/2069/1/012039.

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Abstract A DOE (Design of Experiments) is the laying out of a detailed experimental plan in advance of doing the experiment. Optimal DOEs maximize the amount of information that can be obtained for a given amount of experimental effort. The traditional DOE methodology is waterfall-type methodology implying a sequential and linear life-cycle process. The success of the experiment and usefulness of the results are highly dependent on the initial experimental setup and assumptions, and does not allow to go back and change something that was not well-documented or thought upon in the design stage.
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Cheng, Siyuan, Xiangwei Zhang, and Guoxin Yu. "A hybrid surfacing methodology for reverse engineering." Virtual and Physical Prototyping 4, no. 1 (2009): 11–19. http://dx.doi.org/10.1080/17452750802650470.

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9

Cheng, D. L., Kwang-Ting Cheng, D. C. Wang, and M. Marek-Sadowska. "A hybrid methodology for switching activities estimation." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 17, no. 4 (1998): 357–66. http://dx.doi.org/10.1109/43.703825.

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10

Chakraborty, Tanujit, Swarup Chattopadhyay, and Indrajit Ghosh. "Forecasting dengue epidemics using a hybrid methodology." Physica A: Statistical Mechanics and its Applications 527 (August 2019): 121266. http://dx.doi.org/10.1016/j.physa.2019.121266.

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11

Hudic, Aleksandar, Paul Smith, and Edgar R. Weippl. "Security assurance assessment methodology for hybrid clouds." Computers & Security 70 (September 2017): 723–43. http://dx.doi.org/10.1016/j.cose.2017.03.009.

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12

Briones, Francisco Zorrilla, Jaime Sánchez Leal, and Inocente Yuliana Meléndez Pastrana. "Armentum: a hybrid direct search optimization methodology." Journal of Industrial Engineering International 12, no. 4 (2016): 407–17. http://dx.doi.org/10.1007/s40092-016-0159-5.

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13

Liebrock, L. M., and S. P. Goudy. "Methodology for modelling SPMD hybrid parallel computation." Concurrency and Computation: Practice and Experience 20, no. 8 (2008): 903–40. http://dx.doi.org/10.1002/cpe.1214.

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14

Lagonotte, P., F. Soulier, A. Thomas, and S. Martemianov. "Hybrid impedance spectroscopy and transients testing methodology." Journal of Energy Storage 74 (December 2023): 109290. http://dx.doi.org/10.1016/j.est.2023.109290.

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15

Waeto, Salwa, Khanchit Chuarkham, and Arthit Intarasit. "Forecasting Time Series Movement Direction with Hybrid Methodology." Journal of Probability and Statistics 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/3174305.

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Forecasting the tendencies of time series is a challenging task which gives better understanding. The purpose of this paper is to present the hybrid model of support vector regression associated with Autoregressive Integrated Moving Average which is formulated by hybrid methodology. The proposed model is more convenient for practical usage. The tendencies modeling of time series for Thailand’s south insurgency is of interest in this research article. The empirical results using the time series of monthly number of deaths, injuries, and incidents for Thailand’s south insurgency indicate that th
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16

Singh, Prabhdeep. "Enhancing Performance of Hybrid Electric Vehicle using Optimized Energy Management Methodology." International Journal of Data Informatics and Intelligent Computing 2, no. 3 (2023): 1–10. http://dx.doi.org/10.59461/ijdiic.v2i3.74.

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The fuel consumption and the fuel management strategy (PMS) of the hybrid electric vehicle are closely linked (HEV). In this study, a hybrid power management technique and an adaptive neuro-fuzzy inference (ANFIS) method are established. Artificial intelligence represents a huge improvement in electricity management across different energy sources (AI). The main energy source of the hybrid power supply is a proton exchange membrane fuel cell (PEMFC), while its electrical storage devices are a battery bank and an ultracapacitor. The hybrid electric vehicle's power management strategy (PMS) and
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17

Zhang, Xingliang, Fan Yang, Shenheng Xu, Abdul Aziz, and Maokun Li. "Hybrid Polarization-Phase Tuning Methodology for Reflectarray Antennas." IEEE Transactions on Antennas and Propagation 69, no. 9 (2021): 5534–45. http://dx.doi.org/10.1109/tap.2021.3060023.

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18

G, Sekhar Reddy. "Conceptual Design of Data Warehouse using Hybrid Methodology." International Journal of Advanced Trends in Computer Science and Engineering 9, no. 3 (2020): 2567–73. http://dx.doi.org/10.30534/ijatcse/2020/13932020.

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19

López-Ortiz, Enrique J., Fernando Sancho-Caparrini, Miguel Á. Martínez-del-Amor, Luis M. Soria-Morillo, and Juan A. Álvarez-García. "Hybrid agent-based methodology for testing response protocols." Knowledge-Based Systems 222 (June 2021): 107005. http://dx.doi.org/10.1016/j.knosys.2021.107005.

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20

Sahu, Anoop Kumar, Nitin Kumar Sahu, and Atul Kumar Sahu. "Benchmarking CNC Machine Tool Using Hybrid-Fuzzy Methodology." International Journal of Fuzzy System Applications 4, no. 2 (2015): 28–46. http://dx.doi.org/10.4018/ijfsa.2015040103.

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In today's era, managerial decision making has become a very momentous component due to the leverage of attention on achieving organizational goal i.e. enhancing effective utilization of input assets, satisfying customers' demand and minimizing loss (maximize profit). The evaluation of the most appropriate Computer Numerical Control (CNC) machine tool has become one of the key factors for sustaining the organization/manufacturing sectors/production units at competitive global market place. Productivity, precision and accuracy etc. are the most important issues behind adaptation/exploration of
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21

Nalepa, Grzegorz, and Antoni Ligęza. "The HeKatE methodology. Hybrid engineering of intelligent systems." International Journal of Applied Mathematics and Computer Science 20, no. 1 (2010): 35–53. http://dx.doi.org/10.2478/v10006-010-0003-9.

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The HeKatE methodology. Hybrid engineering of intelligent systemsThis paper describes a new approach, the HeKatE methodology, to the design and development of complex rule-based systems for control and decision support. The main paradigm for rule representation, namely, eXtended Tabular Trees (XTT), ensures high density and transparency of visual knowledge representation. Contrary to traditional, flat rule-based systems, the XTT approach is focused on groups of similar rules rather than on single rules. Such groups form decision tables which are connected into a network for inference. Efficien
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22

Teuschl, Gerald, Peter Ebner, Peter Götschl, and Mario Ninaus. "Calibration Methodology and SiL Environment for Hybrid Powertrains." ATZ worldwide 124, no. 9 (2022): 48–53. http://dx.doi.org/10.1007/s38311-022-0823-x.

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23

Kim, Yoon Jae, Sang Min Baek, Won Seok Oh, and Jeong In Go. "Simplified Design Methodology for Frequency Filtering Hybrid Composites." Journal of the Korean Society for Aeronautical & Space Sciences 47, no. 12 (2019): 897–903. http://dx.doi.org/10.5139/jksas.2019.47.12.897.

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24

Merzouk, Soukaina, Abdessamad Cherkaoui, Fatima-zahra Guerss, Abdelaziz Marzak, and Sael Nawal. "Smart Irrigation: case study for Hybrid-SIX methodology." Procedia Computer Science 191 (2021): 524–29. http://dx.doi.org/10.1016/j.procs.2021.07.077.

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25

Yoo, Yongmin, Tak-Sung Heo, Yeongjoon Park, and Kyungsun Kim. "A Novel Hybrid Methodology of Measuring Sentence Similarity." Symmetry 13, no. 8 (2021): 1442. http://dx.doi.org/10.3390/sym13081442.

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The problem of measuring sentence similarity is an essential issue in the natural language processing area. It is necessary to measure the similarity between sentences accurately. Sentence similarity measuring is the task of finding semantic symmetry between two sentences, regardless of word order and context of the words. There are many approaches to measuring sentence similarity. Deep learning methodology shows a state-of-the-art performance in many natural language processing fields and is used a lot in sentence similarity measurement methods. However, in the natural language processing fie
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26

Abdallah, Wissam, Nassib Abdallah, Jean-Marie Marion, Mohamad Oueidat, and Pierre Chauvet. "A Hybrid Methodology for Short Term Temperature Forecasting." International Journal of Intelligence Science 10, no. 03 (2020): 65–81. http://dx.doi.org/10.4236/ijis.2020.103005.

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27

Jacobson, Kevin E., and Marilyn J. Smith. "Carefree Hybrid Methodology for Rotor Hover Performance Analysis." Journal of Aircraft 55, no. 1 (2018): 52–65. http://dx.doi.org/10.2514/1.c034112.

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28

Murray, Alan T., Tony H. Grubesic, Ran Wei, and Elizabeth A. Mack. "A Hybrid Geocoding Methodology for Spatio-Temporal Data." Transactions in GIS 15, no. 6 (2011): 795–809. http://dx.doi.org/10.1111/j.1467-9671.2011.01289.x.

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29

Rivette, M., J.-Y. Hacoët, and P. Mognol. "A graph-based methodology for hybrid rapid design." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 221, no. 4 (2007): 685–97. http://dx.doi.org/10.1243/09544054jem666.

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30

Kraemer, D., L. Hu, A. Muto, X. Chen, G. Chen, and M. Chiesa. "Photovoltaic-thermoelectric hybrid systems: A general optimization methodology." Applied Physics Letters 92, no. 24 (2008): 243503. http://dx.doi.org/10.1063/1.2947591.

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31

Zhang, Liang, Zoe Kaufman, and Matt Leach. "Physics-informed hybrid modeling methodology for building infiltration." Energy and Buildings 320 (October 2024): 114580. http://dx.doi.org/10.1016/j.enbuild.2024.114580.

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32

Panjkovic, Goran. "Hybrid charge preamplifiers—Design methodology and performance limits." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 604, no. 1-2 (2009): 229–33. http://dx.doi.org/10.1016/j.nima.2009.01.057.

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33

Roy, Francis, Claude Gazo, Florence Ossart, and Claude Marchand. "TRIZ Methodology Adapted to Hybrid Powertrains Performances Evaluation." Procedia Engineering 131 (2015): 861–70. http://dx.doi.org/10.1016/j.proeng.2015.12.397.

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34

Elasha, Faris, David Mba, Michael Togneri, Ian Masters, and Joao Amaral Teixeira. "A hybrid prognostic methodology for tidal turbine gearboxes." Renewable Energy 114 (December 2017): 1051–61. http://dx.doi.org/10.1016/j.renene.2017.07.093.

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35

Gerard, Jacqueline Carter, and Frances Lindley Arnold. "Performance Improvement with a Hybrid FOCUS-PDCA Methodology." Joint Commission Journal on Quality Improvement 22, no. 10 (1996): 660–72. http://dx.doi.org/10.1016/s1070-3241(16)30273-5.

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36

Marin, Mauricio, Veronica Gil-Costa, Alonso Inostrosa-Psijas, and Carolina Bonacic. "Hybrid capacity planning methodology for web search engines." Simulation Modelling Practice and Theory 93 (May 2019): 148–63. http://dx.doi.org/10.1016/j.simpat.2018.09.016.

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37

Acid, Silvia, and Luis M. de Campos. "A hybrid methodology for learning belief networks: BENEDICT." International Journal of Approximate Reasoning 27, no. 3 (2001): 235–62. http://dx.doi.org/10.1016/s0888-613x(01)00041-x.

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38

Cotik, V., R. Romero Zaliz, and I. Zwir. "A hybrid promoter analysis methodology for prokaryotic genomes." Fuzzy Sets and Systems 152, no. 1 (2005): 83–102. http://dx.doi.org/10.1016/j.fss.2004.10.016.

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39

MURRI, G., and J. SCHAFF. "Fatigue life methodology for tapered hybrid composite flexbeams." Composites Science and Technology 66, no. 3-4 (2006): 499–508. http://dx.doi.org/10.1016/j.compscitech.2005.06.010.

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40

Park, Junghun, Bowon Jung, and Okkyung Choi. "Two-Factor Authentication Methodology using Hybrid Face Recognition." International Journal of Control and Automation 9, no. 1 (2016): 435–44. http://dx.doi.org/10.14257/ijca.2016.9.1.37.

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41

Di, Tria, Ezio Lefons, and Filippo Tangorra. "Academic data warehouse design using a hybrid methodology." Computer Science and Information Systems 12, no. 1 (2015): 135–60. http://dx.doi.org/10.2298/csis140325087d.

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In the last years, data warehousing has got attention from Universities which are now adopting business intelligence solutions in order to analyze crucial aspects of the academic context. In this paper, we present the architecture of a Business Intelligence system for academic organizations. Then, we illustrate the design process of the data warehouse devoted to the analysis of the main factors affecting the importance and the quality level of every University, such as the evaluation of the Research and the Didactics. The design process we describe is based on a hybrid methodology that is larg
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42

Tseng, Chih-Hsiung, Sheng-Tzong Cheng, and Yi-Hsien Wang. "RETRACTED: New hybrid methodology for stock volatility prediction." Expert Systems with Applications 36, no. 2 (2009): 1833–39. http://dx.doi.org/10.1016/j.eswa.2007.12.004.

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43

Aladag, Cagdas Hakan, Erol Egrioglu, and Cem Kadilar. "Forecasting nonlinear time series with a hybrid methodology." Applied Mathematics Letters 22, no. 9 (2009): 1467–70. http://dx.doi.org/10.1016/j.aml.2009.02.006.

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44

Malham, Christelle Bou, Rodrigo Rivera Tinoco, Assaad Zoughaib, Denis Chretien, Mai Riche, and Nathalie Guintrand. "A novel hybrid exergy/pinch process integration methodology." Energy 156 (August 2018): 586–96. http://dx.doi.org/10.1016/j.energy.2018.05.082.

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45

Araújo, Ricardo de A., Sergio Soares, and Adriano L. I. Oliveira. "Hybrid morphological methodology for software development cost estimation." Expert Systems with Applications 39, no. 6 (2012): 6129–39. http://dx.doi.org/10.1016/j.eswa.2011.11.077.

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46

Ali, Rahman, Muhammad Afzal, Maqbool Hussain, et al. "Multimodal hybrid reasoning methodology for personalized wellbeing services." Computers in Biology and Medicine 69 (February 2016): 10–28. http://dx.doi.org/10.1016/j.compbiomed.2015.11.013.

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47

Bezzo, F., S. Macchietto, and C. C. Pantelides. "A general methodology for hybrid multizonal/CFD models." Computers & Chemical Engineering 28, no. 4 (2004): 501–11. http://dx.doi.org/10.1016/j.compchemeng.2003.08.004.

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48

Bezzo, F., and S. Macchietto. "A general methodology for hybrid multizonal/CFD models." Computers & Chemical Engineering 28, no. 4 (2004): 513–25. http://dx.doi.org/10.1016/j.compchemeng.2003.08.010.

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49

Khashei, Mehdi, and Mehdi Bijari. "A New Hybrid Methodology for Nonlinear Time Series Forecasting." Modelling and Simulation in Engineering 2011 (2011): 1–5. http://dx.doi.org/10.1155/2011/379121.

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Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy. However, using ANNs to model linear problems have yielded mixed results, and hence; it is not wise to apply them blindly to any type of data. This is the reason that hybrid methodologies combining linear models such as ARIMA and nonlinear models such as ANNs have been proposed in the literature of time series forecasting. Despite of all advantages of the traditional methodologies for combining ARIMA and ANNs,
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50

Ribó-Pérez, David, Paula Bastida-Molina, Tomás Gómez-Navarro, and Elías Hurtado-Pérez. "Hybrid assessment for a hybrid microgrid: A novel methodology to critically analyse generation technologies for hybrid microgrids." Renewable Energy 157 (September 2020): 874–87. http://dx.doi.org/10.1016/j.renene.2020.05.095.

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